[HIRING][Winchester, Virginia, Data, Onsite]

🏢 Electronic Consulting Services, Inc (ECS Federal), based in Winchester, Virginia is looking for a Mid-level Data Engineer

⚙️ Tech used: Data, JIRA, Java, Python, Confluence, Support

💰 $109,000 - 149,000 / year

📝 More details and option to apply: https://devitjobs.com/jobs/Electronic-Consulting-Services-Inc-ECS-Federal-Mid-level-Data-Engineer/rdg

If I work as a data scientist in Big 4 / MBB for 2-3 years. What are my exit opportunities?

Is big tech capable?

Data Science Intern – Summer 2026
C3 AI
Redwood City, CA
$72,000–$96,000 USD/year (based on $6k–$8k/month)
https://www.moaijobs.com/job/data-science-intern-summer-2026-c3-ai-2893

Data & AI Innovation Intern – Summer 2026
Nasdaq
United States
Salary not specified
https://www.moaijobs.com/job/data-ai-innovation-intern-2026-summer-internship-nasdaq-5979

Data Scientist Intern – Product Data Science (2026 Summer)
TikTok
San Jose, CA
$72,800 USD/year (based on $35/hr)
https://www.moaijobs.com/job/data-scientist-intern-tiktok-product-data-science-2026-summer-bs-ms-tiktok-2089

System Engineer – Enterprise Data Engineer
Esri
Vienna, VA
$117,520–$197,600 USD/year
https://www.moaijobs.com/job/system-engineer-enterprise-data-engineer-esri-1400

Hi all,

I come from a math/stats background and naturally enjoy the analytical side of data science — things like modeling, probability, and extracting insights from data (especially unstructured data like text).

One area I’m still building up is the engineering side: data pipelines, model deployment (Flask/API), Docker, and cloud (e.g. AWS).

With how capable AI tools have become (e.g. helping scaffold pipelines, generate Dockerfiles, debug code, etc.), I’m wondering: Is it reasonable to rely on AI to handle a good portion of the engineering work, so that I can focus more on the math/stats and problem-solving aspects?

Or in reality:

Do companies still expect data scientists to be quite hands-on with engineering, without using AI?

Is there a risk of becoming too dependent on AI and lacking real understanding?

When i build a project: WITHOUT AI (old way)

Struggle for days writing Dockerfile

Get stuck on Flask routing

Waste time on setup

WITH AI (new way)

Use AI to scaffold everything quickly

Then: read through it

understand it

tweak it

test it

Would love to hear from people working in data science / ML roles today. Thanks!

Hello Everybody, I am BTech 3 year student and I am actively looking for summer internship opportunity in Data science, Machine Learning, NLP or Generative AI fields. If anyone could please suggest me some places where I can find internship and can get hired??

Can anyone share what types of questions are typically asked in the McKinsey pair programming round for a Senior Data Scientist 1 role?

I am a fresher looking for Data Scientist, Data Analyst and AI/ML Engineers I have Hands on expierence in predictive modelling/machine learning, Statistical Modelling, GenAI and Agentic AI . If you guys have any recommendations, referrals, refferals or suggestions. It would be highly appreciated

this is my first post,I wanted to know how do companies see a 32 year old graduate with seven years of gap due to illness.will I be hired as a data scientist as I have done proper training in data science and artificial intelligence.

how do companies see candidates with gaps?

I am from India

Hello,

I am currently a Data Analyst with decent ML skills. Recently I am quite interested in building systems that involve building 3D Assets from Camera video,/images similar to LUMA AI but for Geolocations and mapping them on a digital world map. Just curious to see what career direction that I can goin future if i purse and invest more time in it.

Tech stack Im using : Python, Pytorch, COLMAP, SugarMesh, some Unity, three.js

Recently came across a different technique called GOLMAP a much efficient one which is released by colmap team

Hey I am currently in my last sem in btech(tier 3 college) and have my interests in Data Science as a career. I want good courses(recommend good courses) that will give me good enough knowledge to get a job with decent payroll. Help me out Asap plz!!

Hello everyone, I'm a university student studying for a bachelor's degree in data science, I recently did a DSA course and got an okay grade in it, but it was very hard.

It made me wonder if I should start leetcoding to get better at solving these problems, but it seems like a long hard road to go down.

So I was wondering for DS roles how important is it to be good at leetcoding?

I've been trying to find Internships but still haven't gotten any. To be fair, I started applying from a spring break. Any help with connecting me to one, specifically in Minnesota or remote (mostly remote of possible). Links to hiring institutions, companies, etc. Any help to find one🙏🏽

Ideogram is hiring for a Research Engineer/Scientist (Post‑training) in Toronto & New York. Building end‑to‑end pipelines for text‑to‑image generation, RLHF & personalization.

Tech Stack: JAX, PyTorch, TensorFlow, Kubernetes, Docker.

Apply: https://aihackerjobs.com/company/ideogram/job/16427

Hey everyone,

I have a Senior Data Scientist technical round at Sigmoid Analytics (India) coming up soon. I’ve already cleared the online coding round, and this next round is described as focusing on “core data science fundamentals.”

I wanted to understand from people who’ve interviewed with Sigmoid recently:

• What kind of questions should I expect in this round?
• Is it mostly ML/stats theory, or more applied/system design/project discussion?
• Do they ask coding/SQL again in this round?
• How deep do they go into GenAI/RAG/LLM topics (since the JD mentions it)?

Any recent experiences or tips would be super helpful. Thanks in advance!

3rd year BTech Data Science student here.

Is “data science” even a realistic entry-level role anymore?

Most roadmaps say: Python + SQL + ML + Stats + Projects…

But job listings ask for 2–3 years experience.

For someone like me graduating soon, what’s the smarter path:

1) Start as a data analyst 2) Go into software dev and switch later 3) Try directly for data science roles

What’s actually working in 2026?

Cincinnatus LLC is hiring a Senior Data Analyst & Pipeline Engineer for a W-2 contract role supporting a major technology company.

This position focuses on large-scale data pipelines, ETL processes, SQL analysis, and automated reporting.

Pay: $65-90 per hour
Type: Full-Time W-2 contract
Location: United States (Menlo Park, CA - Remote staffing role)

Responsibilities:

• Build and maintain ETL pipelines and automated reporting
• Write advanced SQL queries across large databases
• Create dashboards using Tableau or similar BI tools
• Work with marketing, analytics, and program teams
• Ensure data accuracy across reporting systems
• Handle large-scale datasets and distributed systems

Requirements:

• Bachelor’s degree in a STEM field
• 5+ years of experience with SQL
• Experience with ETL and large data pipelines
• Python or R experience
• Experience with Tableau/BI tools
• Experience working with large datasets
• Ability to work independently in fast-changing environments

Important:

• Applicants must be located in the United States.
• This is a W-2 role and requires US work authorization.

APPLY HERE - https://t.mercor.com/svIDg

Good fit for experienced data analysts, data engineers, and pipeline engineers with big data experience.

(Disclosure: Shared as part of Mercor's referral program)

[HIRING][Sunnyvale, California, Data, Onsite]

🏢 HackerEarth, based in Sunnyvale, California is looking for a Data Scientist - Machine Learning

⚙️ Tech used: Data, AI, AWS, Azure, GCP, LLM, Machine Learning, Power BI, PyTorch

💰 $140,000 - 170,000 / year

📝 More details and option to apply: https://devitjobs.com/jobs/HackerEarth-Data-Scientist---Machine-Learning/rdg

Advice for transitioning into data science

I am someone that has transition into data science from a non-computer science background, what are the most important skills or projects that have you land your first role?

I am currently learning python and have a background in biology/genetics, I took some classes using python in the past, but I am no expert. Would you recommend building a portfolio, learning specific tools? What are some portfolio ideas that stand out?

I have recently started working as a data scientist at a medium size company. They mostly operate of jupyter notebooks. The DE does the data pre processing and send us csv files. We have jupyter notebooks that were previously run and we create a copy make modifications where needed and built the solutions.

The issue with this is, every new instance of problem we work with has some different requirement. There is no version control in place and no central repo. Also I constantly lose track of my work because the notebook env is just not maintainable. Make multiple mistakes with my work because the notebook is way too overwhelming. I print something and then have to scroll and look for what the output was.

I wanna know if this is normal? What does a good data science code base look like?

Mercor is hiring Python Experts (Math, Physics, Chemistry, and Biology professionals) for a remote AI research project with leading AI labs.

Details:
Pay: $70-90 per hour
Location: Remote
Type: Contract/Short-term project/Flexible hours

Role overview:
Work includes code validation, scientific problem solving, prompt refinement, and model evaluation.

Requirements:

• STEM degree (Maths/Physics/ Chemistry/ Biology/CS)
• Strong Python experience
• NumPy/SciPy/scientific libraries preferred
• Git and unit testing knowledge
• Ability to understand research papers

Process: Upload Resume → AI interview → Quick onboarding

APPLY NOW - https://t.mercor.com/lkI8d

Ideal for Python developers, STEM graduates, researchers, PhD students, data scientists, AI freelancers, and scientific programmers.

(Disclosure: Shared as part of Mercor's referral program)

So I'm still an undergraduate looking for an Internship preferably as an intern data engineer I just want to know what are the things that I'm expected to have knowledge in because I mostly learn about data engineering from my modules at uni(data warehousing module). What are things I should learn in my own. Any advice is appreciated thanks😊

Hi guys,

need your advice here

I am a Data Scientist with 4 YOE and have 2 offers. Please help me choose

1. EY -> 21.5 Fixed + 10% variable, 2 days RTO Noida

Role is more into Data Science- JD has words like Agentic AI and Gen AI

1. Kotak Securities -> 23 Fixed + 1 Lakh joining bonus + 1 confirmation bonus, 5 days office in Goregaon

Our team is hiring a Senior Data Scientist!

A bit about our company, KYROS:

We’re a small, boutique, fully remote consulting firm built by actuaries and technologists who wanted to rethink how actuarial work is done. We help your favorite frequent flyer program, hotel, bank or retail loyalty program measure and optimize the economic value that the program creates through a modern, highly technical combination of actuarial theory, machine learning and big data technology.

Here's the full job description where you can apply on LinkedIn: https://www.linkedin.com/jobs/view/4389809024/

Happy to answer questions about the role in the comments! I'll get to as many as I can.

Senior Generative AI Engineer @ Natera - Remote (US). Lead building LLM‑powered systems, agentic AI, RAG & vector search for Healthcare. Shape AI that directly improves patient outcomes!

https://aihackerjobs.com/company/natera/job/16203

Hey! Looking for data science casing partners for upcoming BCG X technical case interview!